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機器學習/人工智慧診斷市場預測至 2032 年：按組件、診斷類型、技術、應用、最終用戶和地區進行的全球分析

Machine learning / AI diagnostics Market Forecasts to 2032 - Global Analysis By Component (Software, Hardware and Services), Diagnostic Type, Technology, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，全球機器學習/人工智慧診斷市場預計在 2025 年達到 17 億美元，到 2032 年將達到 81 億美元，預測期內的複合年成長率為 24.6%。

機器學習/人工智慧診斷是指應用人工智慧演算法分析醫療數據，輔助疾病檢測、診斷和決策。這些系統從大量資料集（包括醫學影像、病歷和檢測結果）中學習，識別指示健康狀況的模式和異常。透過自動化複雜的分析，人工智慧診斷可以提高臨床工作流程的準確性、速度和一致性。它們支援放射科、病理科、循環系統和其他專業，提供預測性洞察並減少診斷錯誤。雖然人工智慧診斷並非旨在取代醫療專業人員，但它可以增強人類的專業知識，並成為改善醫療環境中患者預後的有力工具。

對早期和準確診斷的需求日益增加

對早期疾病檢測和精準醫療的日益重視，推動了人工智慧診斷的應用。機器學習演算法能夠分析海量醫療資料集，識別細微的模式和異常，從而實現更快、更準確的診斷。這種能力對於癌症和心血管疾病等時間敏感性疾病尤其重要。隨著醫療保健系統優先考慮預防性護理並減少診斷錯誤，人工智慧工具對於增強臨床決策和改善患者預後至關重要。

有限的臨床檢驗

儘管AI診斷前景光明，但有限的臨床檢驗仍是其發展的主要限制因素。許多演算法缺乏針對不同患者群體的廣泛真實世界臨床試驗，這引發了人們對其可靠性和普遍性的擔憂。監管障礙以及嚴格的同行評審研究需求阻礙了其應用。如果沒有確切的臨床證據，醫療服務提供者可能不願意將AI工具納入常規實務。

深度學習演算法的進展

深度學習的快速發展為人工智慧診斷開啟了全新的可能性。增強型神經網路如今能夠以前所未有的精確度處理複雜的醫學影像、基因組數據和電子健康記錄。這些創新實現了預測建模、個人化治療建議和即時診斷支援。隨著演算法變得越來越複雜且易於解讀，它們也越來越容易融入臨床工作流程。這些進步預計將促進跨學科創新，使人工智慧診斷更易於獲取、更具可擴展性，並在全球醫療保健領域發揮更大的影響力。

實施成本高

高昂的實施成本對人工智慧診斷的廣泛應用構成了重大威脅。基礎設施升級、資料整合、演算法訓練以及合規監管標準等相關費用可能令人望而卻步，尤其對於規模較小的醫療機構。此外，持續的維護和員工培訓也加重了財務負擔。如果沒有合適的資金籌措和報銷模式，許多醫療機構可能難以證明投資的合理性，從而限制市場成長。

COVID-19的影響：

COVID-19疫情凸顯了對快速、可擴展的遠距離診斷解決方案的需求，並加速了人們對人工智慧診斷的興趣。人工智慧工具被用於分析胸部掃描結果、預測病情進展並有效率地對患者進行分診。然而，這場危機也暴露了數據品質和演算法適應性的限制。疫情雖然促進了技術創新和應用，但也凸顯了嚴格檢驗和倫理部署的重要性。疫情過後，人工智慧診斷將持續發展，塑造一個具有韌性、技術主導的醫療保健體系。

診斷實驗室部分預計將成為預測期內最大的部分

診斷實驗室細分市場預計將在預測期內佔據最大市場佔有率，這得益於其在臨床檢測和數據生成中的核心作用。這些實驗室處理大量的醫學影像、病理切片和檢測結果，這些是機器學習演算法的理想輸入。整合人工智慧工具有助於實驗室提高吞吐量，減少人為錯誤，並提供更快、更準確的結果。這些實驗室擁有完善的基礎設施和豐富的數據環境，使其成為人工智慧應用的首選，從而推動了其市場佔有率的大幅成長。

預測期間內預計複合年成長率最高的預測部分

隨著人工智慧工具擴大被用於預測疾病進展、治療反應和患者預後，預計預後預測領域將在預測期內呈現最高成長率。這些預測性洞察有助於臨床醫生客製化干涉措施並最佳化護理計劃。隨著個人化醫療和基於價值的照護需求日益成長，預後預測模型具有巨大的臨床和經濟價值。它們推動了醫療保健從被動轉向主動的轉變，從而刺激了該領域的快速成長和創新。

佔比最大的地區：

在預測期內，由於醫療基礎設施的不斷擴張、疾病負擔的不斷加重以及政府的支持措施，亞太地區預計將佔據最大的市場佔有率。中國、印度和日本等國家正大力投資數位醫療和人工智慧技術。該地區龐大的患者群體和日益普及的遠端醫療為人工智慧的整合創造了肥沃的土壤。戰略夥伴關係和區域創新將進一步推動市場成長，使亞太地區成為人工智慧診斷領域的全球領導者。

複合年成長率最高的地區：

預計北美地區在預測期內將實現最高的複合年成長率，這得益於其先進的醫療體系、強大的研發能力和良好的法規結構。該地區受益於人工智慧技術的早期應用、對新興企業的強勁投資以及電子健康記錄的廣泛應用。科技公司與醫療機構之間的合作正在推動創新。此外，人們越來越意識到人工智慧在減少診斷錯誤和改善治療效果方面的潛力，這推動了其在美國和加拿大的快速擴張。

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目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 研究途徑
  • 研究材料
    • 主要研究資料
    • 次級研究資訊來源
    • 先決條件

第3章市場走勢分析

  • 驅動程式
  • 抑制因素
  • 機會
  • 威脅
  • 技術分析
  • 應用分析
  • 最終用戶分析
  • 新興市場
  • COVID-19的影響

第4章 波特五力分析

  • 供應商的議價能力
  • 買方的議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭對手之間的競爭

5. 全球機器學習/人工智慧診斷市場（按組件）

  • 軟體
    • 診斷影像軟體
    • 電子健康記錄 (EHR) 整合工具
    • 實驗室資訊管理系統（LIMS）
  • 硬體
    • 影像設備
    • 診斷設備
  • 服務
    • 諮詢服務
    • 維護和支援服務
    • 整合和實施服務

6. 全球機器學習/人工智慧診斷市場（按診斷類型）

  • 放射學
    • X光影像
    • 電腦斷層掃描
  • 病理
    • 組織病理學
    • 細胞病理學
  • 心臟病學
    • 心電圖分析
    • 心臟超音波圖
  • 神經病學
    • 腦部影像
    • 腦電圖分析
  • 腫瘤學
    • 腫瘤檢測
    • 切片檢查分析
  • 胸部和肺部
    • 肺部影像檢查
    • 呼吸功能分析

7. 全球機器學習/人工智慧診斷市場（按技術）

  • 機器學習
  • 深度學習
  • 自然語言處理（NLP）
  • 電腦視覺
  • 情境感知計算

第8章全球機器學習/人工智慧診斷市場（按應用）

  • 疾病檢測
  • 預後
  • 治療計劃
  • 監測和後續行動

9. 全球機器學習/人工智慧診斷市場（按最終用戶）

  • 醫院
  • 研究機構
  • 診斷實驗室
  • 居家照護環境

第 10 章全球機器學習/人工智慧診斷市場（按地區）

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第11章 重大進展

  • 協議、夥伴關係、合作和合資企業
  • 收購與合併
  • 新產品發布
  • 業務擴展
  • 其他關鍵策略

第12章 公司概況

  • Siemens Healthineers
  • Paige AI
  • GE HealthCare
  • Qure.ai
  • Koninklijke Philips
  • Lunit
  • Aidoc
  • IBM
  • Nanox Imaging
  • InformAI
  • Riverain Technologies
  • Enlitic
  • VUNO Inc.
  • AliveCor
  • Digital Diagnostics
Product Code: SMRC31326

According to Stratistics MRC, the Global Machine learning / AI diagnostics Market is accounted for $1.7 billion in 2025 and is expected to reach $8.1 billion by 2032 growing at a CAGR of 24.6% during the forecast period. Machine learning/AI diagnostics refers to the application of artificial intelligence algorithms to analyze medical data and assist in disease detection, diagnosis, and decision-making. These systems learn from vast datasets-such as medical images, patient records, and lab results-to identify patterns and anomalies that may indicate health conditions. By automating complex analyses, AI diagnostics enhance accuracy, speed, and consistency in clinical workflows. They support radiology, pathology, cardiology, and other specialties, offering predictive insights and reducing diagnostic errors. While not a replacement for medical professionals, AI diagnostics serve as powerful tools to augment human expertise and improve patient outcomes across healthcare settings.

Market Dynamics:

Driver:

Rising Demand for Early and Accurate Diagnosis

The growing emphasis on early disease detection and precision medicine is driving the adoption of AI diagnostics. Machine learning algorithms can analyze vast medical datasets to identify subtle patterns and anomalies, enabling faster and more accurate diagnoses. This capability is especially valuable in time-sensitive conditions like cancer and cardiovascular diseases. As healthcare systems prioritize preventive care and reduce diagnostic errors, AI-powered tools are becoming indispensable in enhancing clinical decision-making and improving patient outcomes.

Restraint:

Limited Clinical Validation

Despite promising capabilities, limited clinical validation remains a major restraint for AI diagnostics. Many algorithms lack extensive real-world testing across diverse patient populations, raising concerns about reliability and generalizability. Regulatory hurdles and the need for rigorous peer-reviewed studies slow down adoption. Without robust clinical evidence, healthcare providers may hesitate to integrate AI tools into routine practice, especially in high-stakes environments.

Opportunity:

Advancements in Deep Learning Algorithms

Rapid advancements in deep learning are unlocking new opportunities in AI diagnostics. Enhanced neural networks can now process complex medical images, genomic data, and electronic health records with unprecedented accuracy. These innovations enable predictive modeling, personalized treatment recommendations, and real-time diagnostic support. As algorithms become more sophisticated and interpretable, their integration into clinical workflows becomes smoother. This evolution is expected to drive innovation across specialties, making AI diagnostics more accessible, scalable, and impactful in global healthcare.

Threat:

High Implementation Costs

High implementation costs pose a significant threat to the widespread adoption of AI diagnostics. Expenses related to infrastructure upgrades, data integration, algorithm training, and compliance with regulatory standards can be prohibitive, especially for smaller healthcare providers. Additionally, ongoing maintenance and staff training add to the financial burden. Without adequate funding or reimbursement models, many institutions may struggle to justify the investment, thus it limits market growth.

Covid-19 Impact:

The COVID-19 pandemic accelerated interest in AI diagnostics by highlighting the need for rapid, scalable, and remote diagnostic solutions. AI tools were deployed to analyze chest scans, predict disease progression, and triage patients efficiently. However, the crisis also exposed limitations in data quality and algorithm adaptability. While the pandemic catalyzed innovation and adoption, it underscored the importance of robust validation and ethical deployment. Post-pandemic, AI diagnostics continue to evolve, shaping resilient and tech-driven healthcare systems.

The diagnostic laboratories segment is expected to be the largest during the forecast period

The diagnostic laboratories segment is expected to account for the largest market share during the forecast period due to its central role in clinical testing and data generation. These labs handle vast volumes of medical images, pathology slides, and lab results-ideal inputs for machine learning algorithms. By integrating AI tools, laboratories can enhance throughput, reduce human error, and deliver faster, more accurate results. Their established infrastructure and data-rich environment make them prime candidates for AI adoption, driving significant market share.

The prognosis prediction segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the prognosis prediction segment is predicted to witness the highest growth rate because AI-powered tools are increasingly used to forecast disease progression, treatment response, and patient outcomes. These predictive insights help clinicians tailor interventions and optimize care plans. With growing demand for personalized medicine and value-based care, prognosis prediction models offer immense clinical and economic value. Their ability to transform reactive care into proactive management is fueling rapid growth and innovation in this segment.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market share due to its expanding healthcare infrastructure, rising disease burden, and supportive government initiatives. Countries like China, India, and Japan are investing heavily in digital health and AI technologies. The region's large patient population and increasing adoption of telemedicine create fertile ground for AI integration. Strategic partnerships and local innovation further accelerate market growth, positioning Asia Pacific as a global leader in AI diagnostics.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR owing to advanced healthcare systems, strong R&D capabilities, and favorable regulatory frameworks. The region benefits from early adoption of AI technologies, robust investment in startups, and widespread use of electronic health records. Collaborations between tech companies and medical institutions foster innovation. Additionally, growing awareness of AI's potential to reduce diagnostic errors and improve outcomes is propelling rapid expansion across the U.S. and Canada.

Key players in the market

Some of the key players in Machine learning / AI diagnostics Market include Siemens Healthineers, Paige AI, GE HealthCare, Qure.ai, Koninklijke Philips, Lunit, Aidoc, IBM, Nanox Imaging, InformAI, Riverain Technologies, Enlitic, VUNO Inc., AliveCor and Digital Diagnostics.

Key Developments:

In September 2025, Lantheus Holdings and GE HealthCare have entered into an exclusive licensing agreement granting GE HealthCare rights to develop, manufacture, and commercialize Lantheus' prostate cancer imaging agent, PYLARIFY(R) (piflufolastat F18), in Japan. This partnership aims to enhance prostate cancer diagnostics in Japan, addressing a significant clinical need in the world's third-largest prostate cancer market.

In April 2025, IBM and Tokyo Electron (TEL) have renewed their collaboration with a new five-year agreement, focusing on advancing semiconductor and chiplet technologies to support the demands of generative AI. This partnership leverages IBM's expertise in semiconductor process integration and TEL's leading-edge equipment to explore smaller nodes and chiplet architectures, aiming to achieve the performance and energy efficiency requirements for the future of generative AI.

Components Covered:

  • Software
  • Hardware
  • Services

Diagnostic Types Covered:

  • Radiology
  • Pathology
  • Cardiology
  • Neurology
  • Oncology
  • Chest & Lung

Technologies Covered:

  • Machine Learning
  • Deep Learning
  • Natural Language Processing (NLP)
  • Computer Vision
  • Context-Aware Computing

Applications Covered:

  • Disease Detection
  • Prognosis Prediction
  • Treatment Planning
  • Monitoring & Follow-up

End Users Covered:

  • Hospitals
  • Research Institutions
  • Diagnostic Laboratories
  • Home Care Settings

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Technology Analysis
  • 3.7 Application Analysis
  • 3.8 End User Analysis
  • 3.9 Emerging Markets
  • 3.10 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Machine learning / AI diagnostics Market, By Component

  • 5.1 Introduction
  • 5.2 Software
    • 5.2.1 Diagnostic Imaging Software
    • 5.2.2 Electronic Health Records (EHR) Integration Tools
    • 5.2.3 Laboratory Information Management Systems (LIMS)
  • 5.3 Hardware
    • 5.3.1 Imaging Devices
    • 5.3.2 Diagnostic Instruments
  • 5.4 Services
    • 5.4.1 Consulting Services
    • 5.4.2 Maintenance & Support Services
    • 5.4.3 Integration & Implementation Services

6 Global Machine learning / AI diagnostics Market, By Diagnostic Type

  • 6.1 Introduction
  • 6.2 Radiology
    • 6.2.1 X-ray Imaging
    • 6.2.2 CT Scans
  • 6.3 Pathology
    • 6.3.1 Histopathology
    • 6.3.2 Cytopathology
  • 6.4 Cardiology
    • 6.4.1 ECG Analysis
    • 6.4.2 Echocardiography
  • 6.5 Neurology
    • 6.5.1 Brain Imaging
    • 6.5.2 EEG Analysis
  • 6.6 Oncology
    • 6.6.1 Tumor Detection
    • 6.6.2 Biopsy Analysis
  • 6.7 Chest & Lung
    • 6.7.1 Pulmonary Imaging
    • 6.7.2 Respiratory Function Analysis

7 Global Machine learning / AI diagnostics Market, By Technology

  • 7.1 Introduction
  • 7.2 Machine Learning
  • 7.3 Deep Learning
  • 7.4 Natural Language Processing (NLP)
  • 7.5 Computer Vision
  • 7.6 Context-Aware Computing

8 Global Machine learning / AI diagnostics Market, By Application

  • 8.1 Introduction
  • 8.2 Disease Detection
  • 8.3 Prognosis Prediction
  • 8.4 Treatment Planning
  • 8.5 Monitoring & Follow-up

9 Global Machine learning / AI diagnostics Market, By End User

  • 9.1 Introduction
  • 9.2 Hospitals
  • 9.3 Research Institutions
  • 9.4 Diagnostic Laboratories
  • 9.5 Home Care Settings

10 Global Machine learning / AI diagnostics Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 Siemens Healthineers
  • 12.2 Paige AI
  • 12.3 GE HealthCare
  • 12.4 Qure.ai
  • 12.5 Koninklijke Philips
  • 12.6 Lunit
  • 12.7 Aidoc
  • 12.8 IBM
  • 12.9 Nanox Imaging
  • 12.10 InformAI
  • 12.11 Riverain Technologies
  • 12.12 Enlitic
  • 12.13 VUNO Inc.
  • 12.14 AliveCor
  • 12.15 Digital Diagnostics

List of Tables

  • Table 1 Global Machine learning / AI diagnostics Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Machine learning / AI diagnostics Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global Machine learning / AI diagnostics Market Outlook, By Software (2024-2032) ($MN)
  • Table 4 Global Machine learning / AI diagnostics Market Outlook, By Diagnostic Imaging Software (2024-2032) ($MN)
  • Table 5 Global Machine learning / AI diagnostics Market Outlook, By Electronic Health Records (EHR) Integration Tools (2024-2032) ($MN)
  • Table 6 Global Machine learning / AI diagnostics Market Outlook, By Laboratory Information Management Systems (LIMS) (2024-2032) ($MN)
  • Table 7 Global Machine learning / AI diagnostics Market Outlook, By Hardware (2024-2032) ($MN)
  • Table 8 Global Machine learning / AI diagnostics Market Outlook, By Imaging Devices (2024-2032) ($MN)
  • Table 9 Global Machine learning / AI diagnostics Market Outlook, By Diagnostic Instruments (2024-2032) ($MN)
  • Table 10 Global Machine learning / AI diagnostics Market Outlook, By Services (2024-2032) ($MN)
  • Table 11 Global Machine learning / AI diagnostics Market Outlook, By Consulting Services (2024-2032) ($MN)
  • Table 12 Global Machine learning / AI diagnostics Market Outlook, By Maintenance & Support Services (2024-2032) ($MN)
  • Table 13 Global Machine learning / AI diagnostics Market Outlook, By Integration & Implementation Services (2024-2032) ($MN)
  • Table 14 Global Machine learning / AI diagnostics Market Outlook, By Diagnostic Type (2024-2032) ($MN)
  • Table 15 Global Machine learning / AI diagnostics Market Outlook, By Radiology (2024-2032) ($MN)
  • Table 16 Global Machine learning / AI diagnostics Market Outlook, By X-ray Imaging (2024-2032) ($MN)
  • Table 17 Global Machine learning / AI diagnostics Market Outlook, By CT Scans (2024-2032) ($MN)
  • Table 18 Global Machine learning / AI diagnostics Market Outlook, By Pathology (2024-2032) ($MN)
  • Table 19 Global Machine learning / AI diagnostics Market Outlook, By Histopathology (2024-2032) ($MN)
  • Table 20 Global Machine learning / AI diagnostics Market Outlook, By Cytopathology (2024-2032) ($MN)
  • Table 21 Global Machine learning / AI diagnostics Market Outlook, By Cardiology (2024-2032) ($MN)
  • Table 22 Global Machine learning / AI diagnostics Market Outlook, By ECG Analysis (2024-2032) ($MN)
  • Table 23 Global Machine learning / AI diagnostics Market Outlook, By Echocardiography (2024-2032) ($MN)
  • Table 24 Global Machine learning / AI diagnostics Market Outlook, By Neurology (2024-2032) ($MN)
  • Table 25 Global Machine learning / AI diagnostics Market Outlook, By Brain Imaging (2024-2032) ($MN)
  • Table 26 Global Machine learning / AI diagnostics Market Outlook, By EEG Analysis (2024-2032) ($MN)
  • Table 27 Global Machine learning / AI diagnostics Market Outlook, By Oncology (2024-2032) ($MN)
  • Table 28 Global Machine learning / AI diagnostics Market Outlook, By Tumor Detection (2024-2032) ($MN)
  • Table 29 Global Machine learning / AI diagnostics Market Outlook, By Biopsy Analysis (2024-2032) ($MN)
  • Table 30 Global Machine learning / AI diagnostics Market Outlook, By Chest & Lung (2024-2032) ($MN)
  • Table 31 Global Machine learning / AI diagnostics Market Outlook, By Pulmonary Imaging (2024-2032) ($MN)
  • Table 32 Global Machine learning / AI diagnostics Market Outlook, By Respiratory Function Analysis (2024-2032) ($MN)
  • Table 33 Global Machine learning / AI diagnostics Market Outlook, By Technology (2024-2032) ($MN)
  • Table 34 Global Machine learning / AI diagnostics Market Outlook, By Machine Learning (2024-2032) ($MN)
  • Table 35 Global Machine learning / AI diagnostics Market Outlook, By Deep Learning (2024-2032) ($MN)
  • Table 36 Global Machine learning / AI diagnostics Market Outlook, By Natural Language Processing (NLP) (2024-2032) ($MN)
  • Table 37 Global Machine learning / AI diagnostics Market Outlook, By Computer Vision (2024-2032) ($MN)
  • Table 38 Global Machine learning / AI diagnostics Market Outlook, By Context-Aware Computing (2024-2032) ($MN)
  • Table 39 Global Machine learning / AI diagnostics Market Outlook, By Application (2024-2032) ($MN)
  • Table 40 Global Machine learning / AI diagnostics Market Outlook, By Disease Detection (2024-2032) ($MN)
  • Table 41 Global Machine learning / AI diagnostics Market Outlook, By Prognosis Prediction (2024-2032) ($MN)
  • Table 42 Global Machine learning / AI diagnostics Market Outlook, By Treatment Planning (2024-2032) ($MN)
  • Table 43 Global Machine learning / AI diagnostics Market Outlook, By Monitoring & Follow-up (2024-2032) ($MN)
  • Table 44 Global Machine learning / AI diagnostics Market Outlook, By End User (2024-2032) ($MN)
  • Table 45 Global Machine learning / AI diagnostics Market Outlook, By Hospitals (2024-2032) ($MN)
  • Table 46 Global Machine learning / AI diagnostics Market Outlook, By Research Institutions (2024-2032) ($MN)
  • Table 47 Global Machine learning / AI diagnostics Market Outlook, By Diagnostic Laboratories (2024-2032) ($MN)
  • Table 48 Global Machine learning / AI diagnostics Market Outlook, By Home Care Settings (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.